A patient activation intervention in primary care for patients with chronic pain on long term opioid therapy: results from a randomized control trial.

BACKGROUND: Given significant risks associated with long-term prescription opioid use, there is a need for non-pharmacological interventions for treating chronic pain. Activating patients to manage chronic pain has the potential to improve health outcomes. The ACTIVATE study was designed to evaluate the effectiveness of a 4-session patient activation intervention in primary care for patients on long-term opioid therapy. METHODS: The two-arm, pragmatic, randomized trial was conducted in two primary care clinics in an integrated health system from June 2015-August 2018. Consenting participants were randomized to the intervention (n = 189) or usual care (n = 187). Participants completed online and interviewer-administered surveys at baseline, 6- and 12- months follow-up. Prescription opioid use was extracted from the EHR. The primary outcome was patient activation assessed by the Patient Activation Measure (PAM). Secondary outcomes included mood, function, overall health, non-pharmacologic pain management strategies, and patient portal use. We conducted a repeated measure analysis and reported between-group differences at 12 months. RESULTS: At 12 months, the intervention and usual care arms had similar PAM scores. However, compared to usual care at 12 months, the intervention arm demonstrated: less moderate/severe depression (odds ratio [OR] = 0.40, 95%CI 0.18-0.87); higher overall health (OR = 3.14, 95%CI 1.64-6.01); greater use of the patient portal's health/wellness resources (OR = 2.50, 95%CI 1.42-4.40) and lab/immunization history (OR = 2.70, 95%CI 1.29-5.65); and greater use of meditation (OR = 2.72; 95%CI 1.61-4.58) and exercise/physical therapy (OR = 2.24, 95%CI 1.29-3.88). At 12 months, the intervention arm had a higher physical health measure (mean difference 1.63; 95%CI: 0.27-2.98). CONCLUSION: This trial evaluated the effectiveness of a primary care intervention in improving patient activation and patient-reported outcomes among adults with chronic pain on long-term opioid therapy. Despite a lack of improvement in patient activation, a brief intervention in primary care can improve outcomes such as depression, overall health, non-pharmacologic pain management, and engagement with the health system. TRIAL REGISTRATION: The study was registered on 10/27/14 on ClinicalTrials.gov (NCT02290223).

Characterizing Unhealthy Alcohol Use Patterns and Their Association with Alcohol Use Reduction and Alcohol Use Disorder During Follow-Up in HIV Care.

Outcomes of PWH with unhealthy alcohol use, such as alcohol use reduction or progression to AUD, are not well-known and may differ by baseline patterns of unhealthy alcohol use. Among 1299 PWH screening positive for NIAAA-defined unhealthy alcohol use in Kaiser Permanente Northern California, 2013-2017, we compared 2-year probabilities of reduction to low-risk/no alcohol use and rates of new AUD diagnoses by baseline use patterns, categorized as exceeding: only daily limits (72% of included PWH), only weekly limits (17%), or both (11%), based on NIAAA recommendations. Overall, 73.2% (95% CI 70.5-75.9%) of re-screened PWH reduced to low-risk/no alcohol use over 2 years, and there were 3.1 (95% CI 2.5-3.8%) new AUD diagnoses per 100 person-years. Compared with PWH only exceeding daily limits at baseline, those only exceeding weekly limits and those exceeding both limits were less likely to reduce and likelier to be diagnosed with AUD during follow-up. PWH exceeding weekly drinking limits, with or without exceeding daily limits, may have a potential need for targeted interventions to address unhealthy alcohol use.

Substance use disorders among primary care patients screening positive for unhealthy alcohol use.

BACKGROUND: Despite high prevalence of polysubstance use, recent data on concurrent alcohol use in patients with specific substance use disorders (SUDs) are lacking. OBJECTIVE: To examine associations between specific SUDs and alcohol consumption levels. METHODS: Using electronic health record data, we conducted a cross-sectional study of 2,720,231 primary care adults screened for alcohol use between 2014 and 2017 at Kaiser Permanente Northern California. Alcohol consumption levels were categorized as no reported use, low-risk use, and unhealthy use (exceeding daily, weekly, or both recommended drinking limits). Using multinomial logistic regression, and adjusting for sociodemographic and health characteristics, we examined the odds of reporting each alcohol consumption level in patients with a prior-year SUD diagnosis (alcohol, cannabis, cocaine, inhalant, opioid, sedative/anxiolytic, stimulant, other drug, nicotine, any SUD except nicotine) compared to those without. RESULTS: The sample was 52.9% female, 48.1% White; the mean age was 46 years (SD = 18). Patients with SUDs were less likely to report low-risk alcohol use relative to no use compared with patients without SUDs. Patients with alcohol or nicotine use disorder had higher odds of reporting unhealthy alcohol use relative to no use; however, patients with all other SUDs (except cocaine) had lower odds. Among patients who reported any alcohol use (n = 861,427), patients with SUDs (except opioid) had higher odds of exceeding recommended limits than those without. CONCLUSION: The associations of unhealthy alcohol use and SUDs suggest that screening for both alcohol and drug use in primary care presents a crucial opportunity to prevent and treat SUDs early.

Patient and provider factors associated with receipt and delivery of brief interventions for unhealthy alcohol use in primary care.

BACKGROUND: Unhealthy alcohol use is a serious and costly public health problem. Alcohol screening and brief interventions are effective in reducing unhealthy alcohol consumption. However, rates of receipt and delivery of brief interventions vary significantly across healthcare settings, and relatively little is known about the associated patient and provider factors. METHODS: This study examines patient and provider factors associated with the receipt of brief interventions for unhealthy alcohol use in an integrated healthcare system, based on documented brief interventions in the electronic health record. Using multilevel logistic regression models, we retrospectively analyzed 287,551 adult primary care patients (and their 2952 providers) who screened positive for unhealthy drinking between 2014 and 2017. RESULTS: We found lower odds of receiving a brief intervention among patients exceeding daily or weekly drinking limits (vs. exceeding both limits), females, older age groups, those with higher medical complexity, and those already diagnosed with alcohol use disorders. Patients with other unhealthy lifestyle activities (e.g., smoking, no/insufficient exercise) were more likely to receive a brief intervention. We also found that female providers and those with longer tenure in the health system were more likely to deliver brief interventions. CONCLUSIONS: These findings point to characteristics that can be targeted to improve universal receipt of brief intervention.

Associations Between Psychiatric Disorders and Alcohol Consumption Levels in an Adult Primary Care Population.

BACKGROUND: Unhealthy alcohol use frequently co-occurs with psychiatric disorders; however, little is known about the relationship between psychiatric disorders and alcohol consumption levels. Understanding varying levels of unhealthy alcohol use among individuals with a variety of psychiatric disorders in primary care would provide valuable insight for tailoring interventions. METHODS: We conducted a cross-sectional study of 2,720,231 adult primary care patients screened for unhealthy alcohol use between 2014 and 2017 at Kaiser Permanente Northern California, using electronic health record data. Alcohol consumption level was classified as no reported use, low-risk use, and unhealthy use, per National Institute on Alcohol Abuse and Alcoholism guidelines. Unhealthy use was further differentiated into mutually exclusive groups: exceeding only daily limits, exceeding only weekly limits, or exceeding both daily and weekly limits. Multivariable multinomial logistic regression models were fit to examine associations between 8 past-year psychiatric disorders (depression, bipolar disorder, anxiety disorder, obsessive-compulsive disorder, schizophrenia, schizoaffective disorder, anorexia nervosa, and bulimia nervosa) and alcohol consumption levels, adjusting for sociodemographic and health characteristics. RESULTS: In the full sample [53% female, 48% White, mean (SD) age = 46 (18) years], patients with psychiatric disorders (except eating disorders), compared to those without, had lower odds of reporting low-risk and unhealthy alcohol use relative to no use. Among patients who reported any alcohol use (n = 861,427), patients with depression and anxiety disorder, compared to those without, had higher odds of exceeding only weekly limits and both limits; patients with bulimia nervosa were also more likely to exceed both limits. CONCLUSIONS: Findings suggest that patients with anxiety disorder, depression, and bulimia nervosa who drink alcohol are more likely to exceed recommended limits, increasing risk of developing more serious problems. Health systems and clinicians may wish to consider implementing more robust screening, assessment, and intervention approaches to support these vulnerable subgroups in limiting their drinking.

Health System-Based Unhealthy Alcohol Use Screening and Treatment Comparing Demographically Matched Participants With and Without HIV.

BACKGROUND: Unhealthy alcohol use among persons living with HIV (PLWH) is linked to significant morbidity, and use of alcohol services may differ by HIV status. Our objective was to compare unhealthy alcohol use screening and treatment by HIV status in primary care. METHODS: Cohort study of adult (≥18 years) PLWH and HIV-uninfected participants frequency matched 20:1 to PLWH by age, sex, and race/ethnicity who were enrolled in a large integrated healthcare system in the United States, with information ascertained from an electronic health record. Outcomes included unhealthy alcohol screening, prevalence, provider-delivered brief interventions, and addiction specialty care visits. Other predictors included age, sex, race/ethnicity, neighborhood deprivation index, depression, smoking, substance use disorders, Charlson comorbidity index, prior outpatient visits, insurance type, and medical facility. Cox proportional hazards models were used to compute hazard ratios (HR) for the outcomes of time to unhealthy alcohol use screening and time to first addiction specialty visit. Poisson regression with robust standard errors was used to compute prevalence ratios (PR) for other outcomes. RESULTS: 11,235 PLWH and 227,320 HIV-uninfected participants were included. By 4.5 years after baseline, most participants were screened for unhealthy alcohol use (85% of PLWH and 93% of HIV-uninfected), but with a lower rate among PLWH (adjusted HR 0.84, 95% CI 0.82 to 0.85). PLWH were less likely, compared with HIV-uninfected participants, to report unhealthy drinking among those screened (adjusted PR 0.74, 95% CI 0.69 to 0.79), and among those who screened positive, less likely to receive brief interventions (adjusted PR 0.82, 95% CI 0.75 to 0.90), but more likely (adjusted HR 1.7, 95% CI 1.2 to 2.4) to have an addiction specialty visit within 1 year. CONCLUSIONS: Unhealthy alcohol use was lower in PLWH, but the treatment approach by HIV status differed. PLWH reporting unhealthy alcohol use received less brief interventions and more addiction specialty care than HIV-uninfected participants.

Correlates of Pregnant Women's Participation in a Substance Use Assessment and Counseling Intervention Integrated into Prenatal Care.

INTRODUCTION: Screening and referral for substance use are essential components of prenatal care. However, little is known about barriers to participation in substance use interventions that are integrated within prenatal care. METHODS: Our study examines demographic and clinical correlates of participation in an initial assessment and counseling intervention integrated into prenatal care in a large healthcare system. The sample comprised Kaiser Permanente Northern California pregnant women with a live birth in 2014 or 2015 who screened positive for prenatal substance use via a self-reported questionnaire and/or urine toxicology test given as part of standard prenatal care (at ~ 8 weeks gestation). RESULTS: Of the 11,843 women who screened positive for prenatal substance use (median age = 30 years; 42% white; 38% screened positive for alcohol only, 20% for cannabis only, 5% nicotine only, 17% other drugs only, and 19% ≥ 2 substance categories), 9836 (83%) completed the initial substance use assessment and counseling intervention. Results from multivariable logistic regression analyses indicated that younger age, lower income, single marital status, and a positive urine toxicology test predicted higher odds of participation, while other/unknown race/ethnicity, greater parity, receiving the screening later in pregnancy, and screening positive for alcohol only or other drugs only predicted lower odds of participation (all Ps < .05). DISCUSSION: Findings suggest that integrated substance use interventions can successfully reach vulnerable populations of pregnant women (e.g., younger, lower income, racial/ethnic minorities). Future research should address whether differences in participation are due to patient (e.g., type of substance used, perceived stigma) or provider factors (e.g., working harder to engage traditionally underserved patients).

Interventions to Reduce Unhealthy Alcohol Use among Primary Care Patients with HIV: the Health and Motivation Randomized Clinical Trial.

BACKGROUND: Unhealthy alcohol use has adverse effects on HIV treatment. Screening, brief intervention, and referral to treatment (SBIRT) has some evidence of efficacy but may not be sufficient for those with low motivation or comorbid substance use. OBJECTIVE: To examine the effectiveness of motivational interviewing (MI) and emailed feedback (EF) among primary care HIV-positive patients, compared with treatment as usual care (UC) only, which included SBIRT. DESIGN: Randomized clinical trial. PARTICIPANTS: Six hundred fourteen adult HIV-positive patients in Kaiser Permanente Northern California who reported prior-year unhealthy alcohol use. INTERVENTION: Participants were randomized to either three sessions of MI (one in person and two by phone), information regarding alcohol risks via EF through a patient portal, or UC alone. MI and EF participants who reported unhealthy alcohol use at 6 months were offered additional MI and EF treatment, respectively. MAIN MEASURES: Participant-reported unhealthy alcohol use (defined as ≥ 4/≥ 5 drinks per day for women/men), alcohol problems at 12 months, based on blinded telephone interviews. Secondary outcomes included drug use and antiretroviral (ART) adherence. KEY RESULTS: At 12 months, there were no overall group differences, but in all three arms, there were declines in unhealthy alcohol use and alcohol-related problems (p < 0.001). Participants reporting low motivation to reduce drinking at baseline were less likely to report unhealthy alcohol use if they received MI vs. EF and UC (p = 0.013). At 6 months, reported illegal drug use/misuse of prescription drugs other than marijuana was lower in the MI arm than EF or UC (p = 0.012). There were no differences in ART adherence between groups. CONCLUSIONS: In a randomized trial of HIV-positive patients using two behavioral interventions compared with SBIRT alone, participants in all three conditions reduced unhealthy alcohol use. MI may provide added benefit for patients with low motivation or who report illegal drug use/misuse of prescription drugs. TRIAL REGISTRATION: NCT01671501 ( ClinicalTrials.gov ).

Patient characteristics associated with treatment initiation and engagement among individuals diagnosed with alcohol and other drug use disorders in emergency department and primary care settings.

Background: Treatment initiation and engagement rates for alcohol and other drug (AOD) use disorders differ depending on where the AOD use disorder was identified. Emergency department (ED) and primary care (PC) are 2 common settings where patients are identified; however, it is unknown whether characteristics of patients who initiate and engage in treatment differ between these settings. Methods: Patients identified with an AOD disorder in ED or PC settings were drawn from a larger study that examined Healthcare Effectiveness Data and Information Set (HEDIS) AOD treatment initiation and engagement measures across 7 health systems using electronic health record data (n = 54,321). Multivariable generalized linear models, with a logit link, clustered on health system, were used to model patient factors associated with initiation and engagement in treatment, between and within each setting. Results: Patients identified in the ED had higher odds of initiating treatment than those identified in PC (adjusted odds ratio [aOR] = 1.89, 95% confidence interval [CI] = 1.73-2.07), with no difference in engagement between the settings. Among those identified in the ED, compared with patients aged 18-29, older patients had higher odds of treatment initiation (age 30-49: aOR = 1.25, 95% CI = 1.12-1.40; age 50-64: aOR = 1.42, 95% CI = 1.26-1.60; age 65+: aOR = 1.27, 95% CI = 1.08-1.49). However, among those identified in PC, compared with patients aged 18-29, older patients were less likely to initiate (age 30-49: aOR = 0.81, 95% CI = 0.71-0.94; age 50-64: aOR = 0.68, 95% CI = 0.58-0.78; age 65+: aOR = 0.47, 95% CI = 0.40-0.56). Women identified in ED had lower odds of initiating treatment (aOR = 0.80, 95% CI = 0.72-0.88), whereas sex was not associated with treatment initiation in PC. In both settings, patients aged 65+ had lower odds of engaging compared with patients aged 18-29 (ED: aOR = 0.61, 95% CI = 0.38-0.98; PC: aOR = 0.42, 95% CI = 0.26-0.68). Conclusion: Initiation and engagement in treatment differed by sex and age depending on identification setting. This information could inform tailoring of future AOD interventions.

Psychiatric comorbidity and Healthcare Effectiveness Data and Information Set (HEDIS) measures of alcohol and other drug treatment initiation and engagement across 7 health care systems.

Background: Psychiatric comorbidity is common among patients with alcohol and other drug (AOD) use disorders. To better understand how psychiatric comorbidity influences AOD treatment access in health care systems, the present study examined treatment initiation and engagement among a large, diverse sample of patients with comorbid psychiatric and AOD use disorders. Methods: This study utilized data from a multisite observational study examining Healthcare Effectiveness Data and Information Set (HEDIS) measures of initiation and engagement in treatment (IET) among patients with AOD use disorders from 7 health care systems. Participants were aged 18 or older with at least 1 AOD index diagnosis between October 1, 2014, and August 15, 2015. Data elements extracted from electronic health records and insurance claims data included patient demographic characteristics, ICD-9 (International Classification of Diseases, Ninth Revision) diagnostic codes, and procedure codes. Descriptive analyses and multivariate logistic regression models were used to examine the relationship between patient-level factors and IET measures. Results: Across health care systems, out of a total of 86,565 patients who had at least 1 AOD index diagnosis during the study period, 66.2% (n = 57,335) patients also had a comorbid psychiatric disorder. Among patients with a comorbid psychiatric disorder, 34.9% (n = 19,998) initiated AOD treatment, and of those, 10.3% (n = 2,060) engaged in treatment. After adjusting for age, sex, and race/ethnicity, patients with comorbid psychiatric disorders were more likely to initiate (odds ratio [OR] = 3.20, 95% confidence interval [CI] = 3.08, 3.32) but no more likely to engage (OR = 0.56, 95% CI = 0.51, 0.61) in AOD treatment, compared with those without a comorbid psychiatric disorder. Conclusions: Findings suggest that identification of comorbid psychiatric disorders may increase initiation in AOD treatment. However, innovative efforts are needed to enhance treatment engagement both generally and especially for individuals without diagnosed psychiatric conditions.

The association between medical comorbidity and Healthcare Effectiveness Data and Information Set (HEDIS) measures of treatment initiation and engagement for alcohol and other drug use disorders.

Background: Medical comorbidity may influence treatment initiation and engagement for alcohol and other drug (AOD) use disorders. We examined the association between medical comorbidity and Healthcare Effectiveness Data and Information Set (HEDIS) treatment initiation and engagement measures.Methods: We used electronic health record and insurance claims data from 7 US health care systems to identify patients with AOD use disorders between October 1, 2014, and August 15, 2015 (N = 86,565). Among patients identified with AOD use disorders in outpatient and emergency department (ED) settings, we examined how Charlson/Deyo comorbidity index scores and medical complications of AOD use were associated with treatment initiation. Among those who initiated treatment in inpatient and outpatient/ED settings, we also examined how comorbidity and AOD use-related medical complications were associated with treatment engagement. Analyses were conducted using generalized estimating equation logistic regression modeling.Results: Among patients identified as having an AOD diagnosis in outpatient and ED settings (n = 69,965), Charlson/Deyo comorbidity index scores of 2 or more were independently associated with reduced likelihood of initiation (risk ratio [RR] = 0.80, 95% confidence interval [CI] = 0.74, 0.86; reference score = 0), whereas prior-year diagnoses of cirrhosis (RR = 1.25, 95% CI = 1.12, 1.35) and pancreatic disease (RR = 1.34, 95% CI = 1.15, 1.56) were associated with greater likelihood of initiation. Among those who were identified in outpatient/ED settings and initiated, higher comorbidity scores were associated with lower likelihood of engagement (score 1: RR = 0.85, 95% CI = 0.76, 0.94; score 2+: RR = 0.61, 95% CI = 0.53, 0.71).Conclusion: Medical comorbidity was associated with lower likelihood of initiating or engaging in AOD treatment, but cirrhosis and pancreatic disease were associated with greater likelihood of initiation. Interventions to improve AOD treatment initiation and engagement for patients with comorbidities are needed, such as integrating medical and AOD treatment.

Factors associated with Healthcare Effectiveness Data and Information Set (HEDIS) alcohol and other drug measure performance in 2014-2015.

Background: Only 10% of patients with alcohol and other drug (AOD) disorders receive treatment. The AOD Initiation and Engagement in Treatment (AOD-IET) measure was added to the national Healthcare Effectiveness Data and Information Set (HEDIS) to improve access to care. This study identifies factors related to improving AOD-IET rates. Methods: We include data from 7 health systems with differing geographic, patient demographic, and organizational characteristics; all used a common Virtual Data Warehouse containing electronic health records and insurance claims data. Multilevel logistic regression models examined AOD-IET among adults (18+). Results: A total of 86,565 patients had an AOD diagnosis qualifying for the HEDIS denominator. The overall initiation rate was 27.9% with wide variation; the overall engagement rate was 11.5% and varied from 4.5% to 17.9%. Women versus men (odds ratio [OR] = 0.81, 95% confidence interval [CI] = 0.76-0.86); Hispanics (OR = 0.85, 95% CI = 0.79-0.91), black/African Americans (OR = 0.82, 95% CI = 0.75-0.90), and Asian Americans (OR = 0.83, 95% CI = 0.72-0.95) versus whites; and patients aged 65+ versus 18-29 (OR = 0.82, 95% CI = 0.74-0.90) had lower odds of initiation. Patients aged 30-49 versus 18-29 (OR = 1.11, 95% CI = 1.04-1.19) and those with prior psychiatric (OR = 1.26, 95% CI = 1.18-1.35) and medical (OR = 1.18, 95% CI = 1.10-1.26) conditions had higher odds of initiation. Identification in primary care versus other departments was related to lower odds of initiation (emergency department [ED]: OR = 1.55, 95% CI = 1.45-1.66; psychiatry/AOD treatment: OR = 3.58, 95% CI = 3.33-3.84; other outpatient: OR = 1.19, 95% CI = 1.06-1.32). Patients aged 30-49 versus 18-29 had higher odds of engagement (OR = 1.26, 95% CI = 1.10-1.43). Patients aged 65+ versus 18-29 (OR = 0.51, 95% CI = 0.43-0.62) and black/African Americans versus whites (OR = 0.64, 95% CI = 0.53-0.77) had lower odds. Those initiating treatment in psychiatry/AOD treatment versus primary care (OR = 7.02, 95% CI = 5.93-8.31) had higher odds of engagement; those in inpatient (OR = 0.40, 95% CI = 0.32-0.50) or other outpatient (OR = 0.73, 95% CI = 0.59-0.91) settings had lower odds. Discussion: Rates of initiation and engagement varied but were low. Findings identified age, race/ethnicity, co-occurring conditions, and department of identification as key factors associated with AOD-IET. Focusing on these could help programs develop interventions that facilitate AOD-IET for those less likely to receive care.

Predictors of Healthcare Effectiveness Data and Information Set (HEDIS) treatment initiation and engagement among patients with opioid use disorder across 7 health systems.

Background: The prevalence of opioid use disorder (OUD) has increased rapidly in the United States and improving treatment access is critical. Among patients with OUD, we examined factors associated with the Healthcare Effectiveness Data and Information Set (HEDIS) performance measures of alcohol and other drug (AOD) treatment initiation and engagement. Methods: Electronic health record and claims data between October 1, 2014, and August 15, 2015, from 7 health systems were used to identify patients (n = 11,490) with a new index OUD diagnosis (no AOD diagnosis prior <60 days) based on International Classification of Diseases (ICD)-9 codes. Multivariable generalized linear models with a logit link clustered on health system were used to examine the associations of patient demographic and clinical characteristics, and department of index diagnosis, with HEDIS measures of treatment initiation and engagement. Results: The prevalence of OUD among all AOD diagnoses varied across health systems, as did rates of AOD initiation (5.7%-21.6%) and engagement (7.6%-24.6%). Those diagnosed in the emergency department (adjusted odds ratio [aOR] = 1.58, 95% confidence interval [CI] = 1.27,1.97) or psychiatry/AOD treatment (aOR = 2.92, 95% CI = 2.47,3.46) were more likely to initiate treatment compared with primary care. Older patients were less likely to initiate (age 50-64 vs. age 18-29: aOR = 0.42, 95% CI = 0.35, 0.51; age 65+ vs. age 18-29: aOR = 0.34, 95% CI = 0.26, 0.43), as were women (aOR = 0.72, 95% CI = 0.62, 0.85). Patients diagnosed in psychiatry/AOD treatment (aOR = 2.67, 95% CI = 1.98, 3.60) compared with primary care were more likely to engage in treatment. Those identified in an inpatient setting (aOR = 0.19, 95% CI = 0.14, 0.27 vs. primary care), those with medical comorbidity (aOR = 0.70, 95% CI = 0.52, 0.95), and older patients (age 50-64 vs. 18-29: aOR = 0.64, 95% CI = 0.46, 0.88; age 65+ vs. 18-29: aOR = 0.36, 95% CI = 0.22, 0.57) were less likely to engage in treatment. Conclusions: Rates of initiation and engagement for OUD patients vary widely with noticeable room for improvement, particularly in this critical time of the opioid crisis. Targeting patient and system factors may improve health system performance, which is key to improving patient outcomes.

Healthcare Effectiveness Data and Information Set (HEDIS) measures of alcohol and drug treatment initiation and engagement among people living with the human immunodeficiency virus (HIV) and patients without an HIV diagnosis.

Background: Problematic use of alcohol and other drugs (AOD) is highly prevalent among people living with the human immunodeficiency virus (PLWH), and untreated AOD use disorders have particularly detrimental effects on human immunodeficiency virus (HIV) outcomes. The Healthcare Effectiveness Data and Information Set (HEDIS) measures of treatment initiation and engagement are important benchmarks for access to AOD use disorder treatment. To inform improved patient care, we compared HEDIS measures of AOD use disorder treatment initiation and engagement and health care utilization among PLWH and patients without an HIV diagnosis. Methods: Patients with a new AOD use disorder diagnosis documented between October 1, 2014, and August 15, 2015, were identified using electronic health records (EHR) and insurance claims data from 7 health care systems in the United States. Demographic characteristics, clinical diagnoses, and health care utilization data were also obtained. AOD use disorder treatment initiation and engagement rates were calculated using HEDIS measure criteria. Factors associated with treatment initiation and engagement were examined using multivariable logistic regression models. Results: There were 469 PLWH (93% male) and 86,096 patients without an HIV diagnosis (60% male) in the study cohort. AOD use disorder treatment initiation was similar in PLWH and patients without an HIV diagnosis (10% vs. 11%, respectively). Among those who initiated treatment, few engaged in treatment in both groups (9% PLWH vs. 12% patients without an HIV diagnosis). In multivariable analysis, HIV status was not significantly associated with either AOD use disorder treatment initiation or engagement. Conclusions: AOD use disorder treatment initiation and engagement rates were low in both PLWH and patients without an HIV diagnosis. Future studies need to focus on developing strategies to efficiently integrate AOD use disorder treatment with medical care for HIV.

The prevalence of Healthcare Effectiveness Data and Information Set (HEDIS) initiation and engagement in treatment among patients with cannabis use disorders in 7 US health systems.

Background: Cannabis use disorders (CUDs) have increased with more individuals using cannabis, yet few receive treatment. Health systems have adopted the Healthcare Effectiveness Data and Information Set (HEDIS) quality measures of initiation and engagement in alcohol and other drug (AOD) dependence treatment, but little is known about the performance of these among patients with CUDs. Methods: This cohort study utilized electronic health records and claims data from 7 health care systems to identify patients with documentation of a new index CUD diagnosis (no AOD diagnosis ≤60 days prior) from International Classification of Diseases, Ninth revision, codes (October 1, 2014, to August 31, 2015). The adjusted prevalence of each outcome (initiation, engagement, and a composite of both) was estimated from generalized linear regression models, across index identification settings (inpatient, emergency department, primary care, addiction treatment, and mental health/psychiatry), AOD comorbidity (patients with CUD only and CUD plus other AOD diagnoses), and patient characteristics. Results: Among 15,202 patients with an index CUD diagnosis, 30.0% (95% confidence interval [CI]: 29.2-30.7%) initiated, 6.9% (95% CI: 6.2-7.7%) engaged among initiated, and 2.1% (95% CI: 1.9-2.3%) overall both initiated and engaged in treatment. The adjusted prevalence of outcomes varied across index identification settings and was highest among patients diagnosed in addiction treatment, with 25.0% (95% CI: 22.5-27.6%) initiated, 40.9% (95% CI: 34.8-47.0%) engaged, and 12.5% (95% CI: 10.0-15.1%) initiated and engaged. The adjusted prevalence of each outcome was generally highest among patients with CUD plus other AOD diagnosis at index diagnosis compared with those with CUD only, overall and across index identification settings, and was lowest among uninsured and older patients. Conclusion: Among patients with a new CUD diagnosis, the proportion meeting HEDIS criteria for initiation and/or engagement in AOD treatment was low and demonstrated variation across index diagnosis settings, AOD comorbidity, and patient characteristics, pointing to opportunities for improvement.

Use of a prescription opioid registry to examine opioid misuse and overdose in an integrated health system.

Strategies are needed to identify at-risk patients for adverse events associated with prescription opioids. This study identified prescription opioid misuse in an integrated health system using electronic health record (EHR) data, and examined predictors of misuse and overdose. The sample included patients from an EHR-based registry of adults who used prescription opioids in 2011 in Kaiser Permanente Northern California, a large integrated health care system. We characterized time-at-risk for opioid misuse and overdose, and used Cox proportional hazard models to model predictors of these events from 2011 to 2014. Among 396,452 patients, 2.7% were identified with opioid misuse and 1044 had an overdose event. Older patients were less likely to meet misuse criteria or have an overdose. Whites were more likely to be identified with misuse, but not to have an overdose. Alcohol and drug disorders were related to higher risk of misuse and overdose, with the exception that marijuana disorder was not related to opioid misuse. Higher daily opioid dosages and benzodiazepine use increased the risk of both opioid misuse and overdose. We characterized several risk factors associated with misuse and overdose using EHR-based data, which can be leveraged relatively quickly to inform preventive strategies to address the opioid crisis.

Alcohol, marijuana, and opioid use disorders: 5-Year patterns and characteristics of emergency department encounters.

BACKGROUND: Changes in substance use patterns stemming from opioid misuse, ongoing drinking problems, and marijuana legalization may result in new populations of patients with substance use disorders (SUDs) using emergency department (ED) resources. This study examined ED admission trends in a large sample of patients with alcohol, marijuana, and opioid use disorders in an integrated health system. METHODS: In a retrospective design, electronic health record (EHR) data identified patients with ≥1 of 3 common SUDs in 2010 (n = 17,574; alcohol, marijuana, or opioid use disorder) and patients without SUD (n = 17,574). Logistic regressions determined odds of ED use between patients with SUD versus controls (2010-2014); mixed-effect models examined 5-year differences in utilization; moderator models identified subsamples for which patients with SUD may have a greater impact on ED resources. RESULTS: Odds of ED use were higher at each time point (2010-2014) for patients with alcohol (odds ratio [OR] range: 5.31-2.13, Ps < .001), marijuana (OR range: 5.45-1.97, Ps < .001), and opioid (OR range: 7.63-4.19, Ps < .001) use disorders compared with controls; odds decreased over time (Ps < .001). Patients with opioid use disorder were at risk of high ED utilization; patients were 7.63 times more likely to have an ED visit in 2010 compared with controls and remained 5.00 (average) times more likely to use ED services. ED use increased at greater rates for patients with alcohol and opioid use disorders with medical comorbidities relative to controls (Ps < .045). CONCLUSIONS: ED use is frequent in patients with SUDs who have access to private insurance coverage and integrated medical services. ED settings provide important opportunities in health systems to identify patients with SUDs, particularly patients with opioid use disorder, to initiate treatment and facilitate ongoing care, which may be effective for reducing excess medical emergencies and ED encounters.

Association of the Affordable Care Act With Smoking and Tobacco Treatment Utilization Among Adults Newly Enrolled in Health Care.

OBJECTIVES: To examine rates of smoking and tobacco treatment utilization by insurance coverage status (Medicaid, commercial, exchange) among newly enrolled patients in the post Affordable Care Act (ACA) era. METHODS: We examined new members who enrolled in Kaiser Permanente Northern California through Medicaid, the California exchange, or nonexchange commercial plans (N=122,298) in the first 6 months of 2014 following ACA implementation. We compared these groups on smoking prevalence and tested whether smokers in each group differed on sociodemographic characteristics and in their utilization of tobacco treatment (pharmacotherapy and counseling) in 2014. RESULTS: Smoking prevalence was higher among Medicaid (22%) than exchange (13%) or commercial (12%) patients (P<0.0001). Controlling for key sociodemographic and clinical characteristics, Medicaid (odds ratio, 1.49; 95% confidence interval, 1.29-1.73) smokers had greater odds of tobacco treatment use than commercial smokers. Other groups at risk for underuse included men, younger patients, Asians, and Latinos. CONCLUSIONS: In this cohort of newly enrolled patients after ACA implementation, Medicaid patients were more likely to be smokers compared with exchange and commercial patients, but they were also more likely to use tobacco treatment. Low tobacco treatment use among exchange and commercial plan smokers, as well as younger men, Asians and Latinos poses a significant obstacle to improving public health and additional targeted outreach strategies may be needed to engage these patients with available health services.

Posttreatment Low-Risk Drinking as a Predictor of Future Drinking and Problem Outcomes Among Individuals with Alcohol Use Disorders: A 9-Year Follow-Up.

BACKGROUND: Treatment for alcohol use disorders (AUDs) has traditionally been abstinence oriented, but new research and regulatory guidelines suggest that low-risk drinking may also be an acceptable treatment outcome. However, little is known about long-term outcomes for patients who become low-risk drinkers posttreatment. This study explores a posttreatment low-risk drinking outcome as a predictor of future drinking and psychosocial outcomes over 9 years. METHODS: Study participants were adults with AUDs at treatment entry who received follow-up interviews 6 months posttreatment intake (N = 1,061) in 2 large randomized studies conducted at Kaiser Permanente Northern California, a large private, nonprofit, integrated health system. Six-month drinking status was defined as abstinent, low-risk (nonabstinent, no 5+ drinking days), or heavy drinking (1 or more days of 5+ drinks). Using logistic regression models, we explored the relationship between past 30-day drinking status at 6 months and odds of being abstinent or a low-risk drinker (compared to heavy drinking), and positive Addiction Severity Index psychosocial outcomes over 9 years (9-year follow-up rate of 73%). RESULTS: Abstainers and low-risk drinkers at 6 months had higher odds of recent abstinence/low-risk drinking over 9 years than heavy drinkers; abstainers had better drinking outcomes than low-risk drinkers. Additionally, among those with interview data, 95% of abstainers and 94% of low-risk drinkers at 6 months were abstinent/low-risk drinkers at 9 years; surprisingly, 89% of heavy drinkers at 6 months were also abstinent/low-risk drinkers although still significantly fewer than the other groups. Abstainers and low-risk drinkers at 6 months had better psychiatric outcomes, and abstainers had better family/social outcomes than heavy drinkers; medical outcomes did not differ. Low-risk drinkers and abstainers showed no reliable differences across psychosocial measures. CONCLUSIONS: The findings suggest that a low-risk drinking outcome may be reasonable over the long-term for some alcohol-dependent individuals receiving addiction treatment.

Trajectories of remission and mortality over 13 years after intake to substance use treatment.

BACKGROUND: Little is known about the relationships between long-term patterns of substance use and mortality risk among substance use disorder (SUD) patients. OBJECTIVE: To determine distinct patterns of remission and relapse of SUD over time and examine their relationship with mortality. METHODS: The study site was Kaiser Permanente of Northern California. Data for 997 adults who entered substance use treatment between 1994 and 1996 and 4,241 non-SUD patients with similar demographic distributions (35% women in both groups) were analyzed. Latent class growth analysis identified distinct remission trajectory groups over 13 years among SUD patients, and survival analyses were conducted to examine the risk of death between remission trajectory groups, and SUD and non-SUD patients within each remission trajectory group. RESULTS: Three distinct remission trajectory groups were identified among SUD patients: 1) early relapse-low remission probabilities; 2) declining remission-decreasing remission probabilities; and 3) stable remission-stable remission probabilities across all time points. Among the SUD patients, the early relapse group had a higher risk of death than those stably remitted; stable and declining remission groups did not differ. Comparisons within each remission trajectory group showed that SUD patients in the early relapse and stable remission groups had higher risks of death compared with non-SUD patients; there were no differences within the declining group. CONCLUSIONS: SUD patients in the stable remission group had lower survival rates compared with non-SUD patients. These findings underline the importance of continuously addressing healthcare needs of individuals with SUD, even in the presence of long-term remission.